Field of the Invention
At least one embodiment in accordance with the present invention relates generally to systems and methods for data center management and design, and more specifically, to systems and methods for managing power consumption of cooling equipment in a data center.
Background Discussion
Centralized data centers for computer, communications, and other electronic equipment contain numerous racks of equipment that require power, cooling, and connections to external communication facilities. Data centers remain one of the largest and fastest growing consumers of electricity in the United States. For example, data centers in total used 91 billion kWh of electrical energy in 2013, and this number is predicted to increase to 140 billion kWh by 2020. Further, in an effort to increase efficiency, the current trend in data center design is to increase power density, thereby delivering more power per rack. The increased density of computing equipment puts strains on the cooling and power systems that service these facilities.
Typically, the power consumed by computer equipment is converted to heat and the cooling requirements of a facility are typically determined based on the power requirements of the facility. In fact, 50% or more of the power consumed by data centers is used by cooling equipment. Typical data centers utilize air plenums under raised floors to distribute cooling air through a data center. One or more computer room air conditioners (CRACs) or computer room air handlers (CRAHs) are typically distributed along the periphery of the data room, and these units draw return air from the room or a ceiling plenum and distribute cooling air beneath the raised floor. Perforated tiles may be placed in front or beneath racks of equipment that are to be cooled to allow the cooling air from beneath the floor to cool equipment within the racks.
Operating a data center in an energy efficient state requires the ability to manage power consumption of both the IT equipment and cooling equipment under various operational states in a practical, yet accurate manner. Current mathematical models for managing power consumption of cooling equipment may be roughly grouped into two categories: empirical models and physics-based models. Empirical models may employ past experimental data or approximate trend-type models to predict future behavior without consideration of certain physical principles, and may be generally based on measured and/or manufacturer-provided data. Polynomial, exponential, power law, logarithmic, and trigonometric functions as well as look-up tables are commonly used as empirical models. The computational simplicity of empirical models enables fast computations, but since these models are based on fitting experimental data for a specific set of operating conditions, these predictions can be very poor for operating conditions that are outside this specific set. Physics-based models may require detailed knowledge of one or more of the components of the data center and/or the layout of the components being monitored, and therefore may come at great computational costs and long simulation times.